System and method for detecting and localizing non-technical losses in an electrical power distribution grid

ABSTRACT

A system and method for detecting theft of power in an electrical distribution grid. The system may include at least two communicating meters which form a transformer area network, a mechanism for measuring current and voltage at the meters, a mechanism for transmitting the measured current and voltage data to a data center with access to an electric grid database, and a mechanism that analyzes the transmitted data to infer unauthorized taking of electrical power.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of co-pending U.S. patent applicationSer. No. 14/304,035, filed Jun. 13, 2014, entitled “SYSTEM AND METHODFOR DETECTING AND LOCALIZING NON-TECHNICAL LOSSES IN AN ELECTRICAL POWERDISTRIBUTION GRID,” which claims the benefit of U.S. Provisional PatentApplication No. 61/834,567, filed Jun. 13, 2013, entitled “SYSTEM ANDMETHOD FOR DETECTING AND LOCALIZING NON-TECHNICAL LOSSES IN ANELECTRICAL POWER DISTRIBUTION GRID,” the disclosures of each of whichare incorporated herein by reference in their entireties.

FIELD OF THE INVENTION

The present invention is directed toward applications of on-gridcommunications for optimizing electrical distribution, and specificallyfor real-time identification and location of non-technical lossesoccurring in a service transformer area network.

BACKGROUND OF THE INVENTION

Electrical Distribution Substations contain one or more SubstationTransformers, which step down the voltage from high transmission linelevels (typically 130 kV to 700 kV) to the medium voltage levels(typically from 4 kV to about 35 kV) at which power is distributed toconsumers within a distribution service area. At the edge of theDistribution Grid are a number of Service Transformers, which transformthe medium voltage of the distribution grid to the low voltages (in theUS, typically 120, 208, 240, 277, or 480) required for commercial,industrial, and residential consumers. Other voltages in addition tosome of these can be used elsewhere in the world. Each ServiceTransformer powers one or more metered loads. A load can be a dwelling,a commercial or industrial building, an element of municipalinfrastructure such as a series of street lamps, or agriculturalapparatus such as irrigation systems.

Other than the wires connecting a consumer load and the associated meterto a service transformer, the service transformer is the outermostelement of the distribution grid before the power is actually deliveredto a consumer. A meter is typically attached at the point where thepower from the service transformer is delivered to a consumer. Servicetransformers can be three-phase, dual-phase, or single phase, as canmeters. Herein the collection of electrical apparatus inclusive from aservice transformer to the collection of at least two communicatingelectrical meters is referred to as a Transformer Area Network (TAN). ATAN can have a radial topology, such as is common in the US, or it canhave a linear or “bus” topology, as is more common in Europe andelsewhere in the world.

Traditionally, reading meters was one of the largest operational costsincurred by electrical utilities. Original electric meters were analogdevices with an optical read-out that had to be manually examinedmonthly to drive the utility billing process. Beginning in the 1970s,mechanisms for digitizing meter data and automating its collection beganto be deployed. These mechanisms evolved from walk-by or drive-bysystems where the meter would broadcast its current reading using ashort-range radio signal, which was received by a device carried by themeter reader. These early systems were known as Automated Meter Readingsystems or AMRs. Later, a variety of purpose-built data collectionnetworks, commonly employing a combination of short-range RF repeatersin a mesh configuration with collection points equipped with broadbandbackhaul means for transporting aggregated readings began to bedeployed.

These networks were capable of two-way communication between the“metering head-end” at a utility service center and the meters at theedge of this data collection network, which is generally called anAdvanced Metering Infrastructure or AMI. AMIs can collect and storereadings frequently, typically as often as every 15 minutes, and canreport them nearly that often. They can read any meter on demandprovided that this feature is used sparingly, and can connect ordisconnect any meter on demand as well. AMI meters can pass signals toconsumer devices for the purpose of energy conservation, demandmanagement, and variable-rate billing. Because the AMI network isseparate from the power distribution grid except for the intersection atthe meters, AMI meters are neither aware of nor sensitive to changes inthe grid topology or certain conditions on the grid. Nonetheless, theintroduction of AMI is generally considered to be the beginning of thedistribution Smart Grid. Additionally, because of the mesh architecturetypically used in the AMIs in the United States, the available bandwidthfor an individual electrical meter to send its own data is quitelimited.

The total billable kilowatt-hours produced by a typical electricaldistribution grid anywhere in the world is substantially less than theactual power distributed, as measured at a distribution substation, overthe billing period. The loss of power can be classified into two groups.Technical losses result from the overall impedance of the distributioninfrastructure, from power-factor mismatch between what the populationof loads requires and what the grid produces at each load point, and thefact that utilities oversupply voltage to ensure that power sags willnot occur during unpredictable peak loads. Utilities can work tominimize these technical losses, but some technical losses areunavoidable.

Non-technical losses of actual power-hours (as opposed to revenue)result from power theft by consumers who avoid or subvert the meteringprocess by tampering with meters or by tapping power lines above themetered load points. Non-technical revenue losses also includenon-payment of bills by customers, and accounting errors by utilities.However, these types of revenue losses are addressed by Meter DataManagement systems integrated with the Advanced Metering Infrastructure.These automated systems have the capability to prevent clerical errors,to immediately cut off service to non-paying customers, and to requirecustomers with poor payment histories to be on a pay-in-advance billingplan. Because AMIs provide little or no information about thegrid-schematic relationship of one electrical meter to another and therelationship between the electrical meter and the service transformersupplying it with power, AMIs are of little value in pinpointing thesource of power theft. Some Smart Meters can detect and reporttampering. On the other hand, the absence of meter readers fromneighborhoods reduces the chance that illegal taps will be seen andreported.

The social and financial costs of power theft are highly variable, inthe developing world, these costs are quite high: sometimes exceeding50% of power delivered from substations. In India, for example, themajor private utilities (Reliance and Tata) report non-technical lossesaround 10%, but the state-owned utilities have losses exceeding 30% inmost cases, according to the India's Maharashtra Electricity RegulationCommission (MERC).

In the developed world, losses from theft represent a relatively smallpercentage of the total generation cost. In the United States, lossesfrom theft have traditionally been estimated at one to three percent ofrevenue, though this figure increases during difficult economic times.

Power theft represents a safety and quality service issue as well as aneconomic issue. Jury-rigging power taps is dangerous and often resultsin injury and even death. Additionally, the jury-rigged taps represent afire hazard. Most significantly the resultant unpredictable loading ofthe distribution grid can cause transformer fires and explosions thatcan result not only in dangerous situations but in major power outages.

Prior art methods for detecting power theft can be divided into threecategories. One category involves comparing voltage and current at ameter with voltage and current at a point of origin for delivery, suchas the service distribution transformer for a neighborhood. Thetechnical losses due to the resistance of the low voltage line betweenthe point of origin and each meter are presumed to be less than apredetermined amount, so that any difference in power loss above thepredetermined amount can be presumed to be due either to theft or toline defects. United States Patent Application Publication No.2012/0265355, titled System and Method for Single and and MultizonalOptimization of Utility Services Delivery and Utilization (incorporatedherein by reference) describes a system of this sort, whereinintelligent software agents at the service transformer collectmeasurements both at the transformer and from other instruments locatedat or incorporated in the electric meters. Theft detection is cited asone of the applications of this system. However, systems involvingplacing agents and instruments at the transformer are less desirablethan would be a system that did not require any devices at thetransformer, because transformers are far less physically accessiblethan meter sockets, and modifying them by adding instrumentation insidethe transformer housing or on the high-voltage side of the transformercan be costly and even dangerous.

A second category involves measuring current and voltage outside themeter of a metered load, and inside the premises of the metered load. Ifmore power is being used on the premises than is being delivered via themeter, then either power is being locally generated on the premises, orthe meter is being bypassed. Methods of this sort are problematic forutilities because a service utility typically does not have access todata from inside the metered load. The consumer would have to agree tothe placement of devices inside the premises.

A third category involves detecting the instantaneous changes in powerusage or minor outages caused by tampering with the distribution linesin order to install an unmetered tap. This category of mechanism failsshort because tampering can be masked by larger events such as alegitimate outage or interruption in service, and because it wouldcreate many false positives.

SUMMARY OF THE INVENTION

The present invention is an apparatus and methods for real-time ornear-real-time detecting and reporting of power theft in such a way thatthe tamper point may be determined to have occurred on the low voltageside of a specific service transformer. In cases of meter tampering thespecific meter or meters involved may be identified. The presentinvention does not require instrumentation of the transformer at theservice delivery point (service transformer). All instruments and theintelligent agents which perform and collect the measurements andprocess the collected data to find evidence of power theft are locatedwhere instruments and intelligence would reside anyway: at theelectrical meter. This is beneficial in that the meter socket istypically easily accessible, and because a smart meter already containsmemory and processors for hosting software agents, already has thecapability of making many of the measurements used by the methods of thepresent invention, and because most smart meters are designed toaccommodate an additional circuit board where the native instruments,communication capabilities, and/or memory and processing capabilitiesare insufficient to support the methods described herein.

U.S. patent application Ser. No. 13/871,944, titled A System and Methodfor inferring Schematic and Topological Properties of an ElectricalDistribution Grid, incorporated herein by reference, describesaugmenting Smart Meters with long-range (Edge-to-Substation) on-gridtransmitters, and also short-range (low voltage, local to the servicetransformer) on grid transceivers. A Smart Meter having both short-rangeand long-range on-grid transmission capability is called a Remote Hub. ASmart Meter having only short-range on-grid capability is called aSubordinate Remote. The term Remotes is used to refer collectively toboth Subordinate Remotes and Remote Hubs. A service transformer having aRemote Hub and zero or more Subordinate Remotes is defined as aTransformer Area Network, or TAN. Further, that application discloses amethod for determining the feeder and phase supplying a Remote Hub withpower based on characteristics of a long-range message transmitted fromthe Remote Hub.

U.S. patent application Ser. No. 13/888,102, titled Methods forDiscovering, Partitioning, Organizing, and Administering CommunicationDevices in a Transformer. Area Network, also incorporated herein byreference, teaches a method of ensuring that all Remote Hubs andSubordinate Remotes in a TAN are, in fact, supplied with power by thesame service transformer, and, in the case of a multi-phase transformer,determining which Remotes are on the same phase as a Remote Hub andwhich Remotes are on a different phase. Additionally, U.S. patentapplication Ser. No. 13/911,849, titled A System and Method forInferring Schematic Relationships between Load Points and ServiceTransformers and incorporated herein by reference, describes a methodfor identifying the specific service transformer and its geospatialcoordinates which supply a given meter socket, and incorporating theassociation and coordinates into a map of the distribution grid. Theutility already knows at least the street address, if not the precisegeospatial coordinates, of every meter. Using the information obtainedfrom the systems and methods in the above-referenced applications, thephysical and schematic origin of a report from a Remote Hub, and thephysical and schematic extent of the Transformer Area Network the RemoteHuh represents, may be very precisely defined. These inventions teach aTransformer Area Network Architecture which is master-slave in nature,wherein one Remote, typically the Remote Hub, contains most of theintelligence, and polls simpler agents on the Subordinate Remotes bothto organize the TAN, and to implement applications on the TAN. Thesystem and methods of the present invention are primarily described interms of such a TAN organization. However, a master-slave networkorganization is only one of the possible network organizations suitablefor hosting the present invention. For example, a peer-to-peertransformer area network is also suitable. A wider peer-to-peer network,such as an AMI mesh network, might also be suitable given that a) thenodes in the network have sufficient information to partition themselveslogically by transformer area, and b) that there is sufficient bandwidthfor sharing the measurements taken by the measurement agents of thepresent invention, as described herein below.

The present invention provides a method for a Remote Hub incommunication with at least one Subordinate Remote, each Remote operableto measure and store voltage at the meter and current passing from themeter to the metered load, to identify indications that power theft isoccurring in the TAN, without placing apparatus either at the servicetransformer of the TAN or inside the premises of the loads powered bythe TAN. For this purpose, the TAN comprises at least two nodes, such asone Remote Hub and one or more Subordinate Remotes, on each phase of theTAN. Further, every load (metered service point) on the TAN has a Remote(or another type of communicating meter) if complete theft protection isto be achieved. The method can be employed with some meters not having aRemote, but some thefts may go undetected in that case, depending on thetopology of the TAN and the location of the unauthorized tap withrespect to the communicating meters. Methods for inferring the existenceand location of illegal taps that do not require taking measurements atthe service transformer of the TAN are taught. Avoiding the need to takemeasurements at the service transformer is desirable because the cost ofonly adding instrumentation at the meters is significantly lower thanthe cost of adding instrumentation at both the meter and thetransformer, as is the cost of maintaining the network when allinstruments and intelligence reside at the meter only. Avoiding the needto place apparatus inside the premises of the metered service point isdesirable because the consent of the consumer is required to placeapparatus inside the premises, and because maintenance of equipmentinside the premises is typically outside the charter of the utility.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and form a part ofthe specification, illustrate the embodiments of the present inventionand, together with the description, serve to explain the principles ofthe invention. In the drawings:

FIG. 1 illustrates a radial-topology transformer area, with anabove-ground transformer and power lines and three metered premises.

FIG. 2 illustrates a bus-topology transformer area with a pad-mountedtransformer, underground power lines, and three metered premises along asingle tap.

FIG. 3 illustrates a radial-topology transformer area with a pad-mountedtransformer, underground power lines, and three metered premises eachwith its own tap.

FIG. 4 illustrates the area of FIG. 1 enhanced to form a TransformerArea Network by the addition of a Remote Hub and to Subordinate Remotes.

FIG. 5 shows the Transformer Area Network of FIG. 4 with the addition ofan illegal unmetered tap used to power a greenhouse.

FIG. 6 shows the electrical detail of a radial Transformer Area Networklike that of FIGS. 4 and 5, with an arbitrary number of metered premises(Nodes) N.

FIG. 7 is a schematic diagram of a system of the present disclosure.

DETAILED DESCRIPTION OF THE INVENTION

Refer to FIG. 1, which illustrates a typical single-phase pole-mountedtransformer 101 connected via aerial power lines 102 to residences 103.In the United States and many other locales, this is a typicalconfiguration, especially in older areas. Power lines to residences aretypically attached to the eaves of the roof, with the power linestraveling downward to the meters 104 in conduit on the exterior of theresidences 103. FIG. 2, by contrast, illustrates a bus topology for thetransformer area, which is more typical in other parts of the world thanin the United States. In FIG. 2, a pad-mounted transformer 201 connectsvia a linear buried line 202 connected to residences 203, 204, and 205at meters 206, 207, and 208 respectively. This topology is common inEurope and elsewhere in the world. A typical installation might servemany more meters than shown: the average number of meters persingle-phase transformer in the US is approximately six (6), but theEuropean average is dozens. FIG. 3 shows a typical US buried-cableinstallation, wherein pad-mounted transformer 301 is connected radiallyvia buried cable 302 to residences 303 at meters 304. These three basicconfigurations, with minor local variations and multi-phase variationsfor industrial and commercial applications, represent most electricaldistribution networks worldwide. The present invention works with minorvariations on all three of these common topologies, as is taught hereinbelow. For the purpose of this teaching, each phase of a three-phasetransformer can be considered as a separate TAN, even though, asdescribed in Ser. No. 13/888,102, a three-phase transformer area mayactually be organized as a single TAN, but wherein the phase of eachnode (e.g. Remote) in the TAN is known, and Edge-to-Substationtransmissions from the TAN are sent on the phase to which they pertain.

Refer now to FIG. 4, where the transformer area of FIG. 1 has beenconverted to a Transformer Area Network by substituting fir the ordinarymeters in FIG. 1 two Subordinate Remotes 402 and 404, and one Remote Hub403. The clocks of the communicating meters of the Transformer AreaNetwork have been synchronized to within a known tolerance, as describedin Ser. No. 13/871,944. Service Transformer 401 does not contain anyadded communication equipment or instruments, and is identical with theService Transformer of FIG. 1. Note that service point/residence 405 hasnearby an unpowered outbuilding 406 such as a barn.

In one embodiment of the invention, a measurement agent resides on eachof Remotes 402, 404, and 403. Each agent periodically measures thedelivered voltage V and flowing current I at its service point. Amonitoring agent which may reside on Remote Hub 403 periodicallycollects the time-stamped current and voltage measurements fromSubordinate Remotes 402 and 404 and from its own measurement agent. Theperiod of the monitoring agent is not required to be the same as theperiod of the measurement agents, but the time at which the measurementsare taken is synchronized to the closest tolerance possible given thecapabilities of the TAN. Both periods are very small with respect to thetime scale of events in a typical AMI network, wherein, for example,meter readings may be transmitted only every fifteen minutes or evenless frequently. The monitoring agent executes a software algorithm thatcompares current and voltage measurements taken at the different metersat the same time and uses them to infer when an unmetered flow ofcurrent is occurring between the transformer and one or more of themetered service points.

In FIG. 5, an unmetered tap 507 has been added at premise 505,electrically between transformer 501 and meter 504. The tap has beenused to electrify outbuilding 506. Not only do such taps cause monetarylosses for the utility, at peak load times they may create a danger oftransformer tires and explosions because the TAN as a whole may bedrawing more power than the rated maximum of the transformer.

FIG. 6 provides electrical detail of a radial Transformer Area Networksuch as that of FIGS. 4 and 5. The TAN of FIG. 6 contains at least twometered service points, or Nodes, herein labeled 1 . . . N. Power source601 supplies transformer 607 with power at a medium voltage, which isstepped down by transformer 607 to the low voltage range accepted by themeters in the transformer area, here represented by meter 627 in Node1(605) and meter 629 in Node N(610). Current 604 represents currentflowing from the power source due to ail the loads on the grid served bypower source 601. Impedance 603 represents the impedance of themedium-voltage grid. The voltage 606 on the low side of transformer 607fluctuates with changes in voltage 602, impedance 603, and current 604.None of these quantities are constant, measureable, or known to thesoftware agents at the meters (such as 627 and 629), but voltage 602 maybe expected to vary around a nominal value within a known range ofacceptable values. For example, a typical nominal value for voltage 602might be 13.4 KV in the United States (though others are possible), anda typical nominal value for voltage 606 might be 240V, though againothers are possible. These nominal values may be known to the softwareagents.

Consider now the components in the rectangle 605 representing Node 1.Node 1 comprises the apparatus delivering power from service transformer607 to meter 627. Interesting measurable quantities are marked on thediagram. Impedance 616 represents the legitimate metered load of thepremise of Node 1, which may vary over time according to what appliancesand devices are in use on the premise. Point 626 is not an actual pieceof equipment, but represents an arbitrary place on the power line fromtransformer 607 to meter 627 where an illegal tap might be installed.Impedance 612, which is normally extremely large when no theft isoccurring, represents a potential unauthorized, unmetered load.Impedances 609 and 613 represent the normal impedance of the power linefrom transformer 607 to meter 627. Voltage 611 represents the voltage athypothetical tap point 626. None of these quantities are known to ormeasureable by the software agents residing at meter 627. Current 614and voltage 615 are measured periodically by the measurement agentresiding at meter 627 and shared on the TAN by the communicationequipment at meter 627. Regardless of the network architecture of theTAN, the sharing is always conducted in such a way that the identity ofthe meter from which the measurements originate and the time themeasurements were taken is known to any receiver of the messages inwhich the measurements are transmitted. Note that element 622 of FIG. 6is not a feature of the TAN, but is an ellipsis indicating that anarbitrary number of additional Nodes could exist between Node 1 605 andNode N 610.

Similarly, consider the components its the rectangle 610 representingNode N. This is the apparatus delivering power horn service transformer607 to meter 629. Impedance 625 represents the legitimate metered loadof the premise of Node N, which may vary over owner time according towhat appliances and devices are in use on the premise. Point 628 is notactual feature of the TAN, but represents an arbitrary place on thepower line from transformer 607 to meter 629 where an illegal tap mightbe installed. Impedance 623, which is normally extremely large when notheft is occurring, represents a possible unauthorized, unmetered load.Impedances 618 and 620 represent the normal impedance of the power linefrom transformer 607 to meter 629. Voltage 619 represents the voltage athypothetical tap point 628. None of these quantities are known to ormeasureable by the software agents residing at meter 629. Current 621and voltage 624 are measured periodically by the measurement agentresiding at meter 629 and shared on the TAN by the communicationequipment at meter 629.

For the purposes of the algorithm of the monitoring agent, it does notmatter whether meter 629, meter 627, or the meter of another Nodebetween 1 and N has the Remote Hub and which meters have SubordinateRemotes, Indeed, as is noted herein above, another type of TANcommunication entirely may be employed, as long as it providessufficient bandwidth for all the meters of the TAN to share theirmeasurements within a sufficiently small period. The TAN may host atleast one monitoring agent somewhere on the TAN and a measuring agent ateach communicating meter. With some network architectures, it may bemore effective to host a monitoring agent in every node. Alternatively,the work of the monitoring agent may be distributed among multiplecommunicating meters. If the monitoring agent does not reside on a meterhaving the capability to send a wide-area message such as anEdge-to-Substation message, then the monitoring agent must transmit acommand to a wide-area enabled device to transmit the anomaly report.

Suppose that an unauthorized load represented by impedance 612 is nowattached at point 626. Voltage 611 will drop because more current (thecurrent drawn by the unauthorized load at 612) is flowing throughimpedance 609. This will also cause a drop in voltage 615. However, thecurrent 614 flowing through impedance 613 does not drop correspondingly.A measurement agent at meter 627, able to measure only current 614 andvoltage 615, will not be able to infer whether the drop in voltage 615is due simply to a drop in voltage 606, or whether it is caused by atheft represented by a drop in voltage 611 and a decrease in impedance612 (which ought to always be very large). However, consider theobservations made by a measurement agent at meter 629. For simplicity,assume that impedance 623 in Node N (610) is properly large no power isbeing stolen in Node N. A measurement agent at meter 621 will observe adrop in voltage 624 due to the drop in voltage 606. A monitoring agentcan use the measured currents 614 and 621 at the meters 627 and 629respectively (and others, if there are more communicating nodes in theTAN) to estimate the proper voltage drop due to each metered load. Oncethe effects of the metered loads (616, 624) have been removed, theadjusted magnitudes of the voltages measured at each meter can becompared. Even though there will be small differences in the lineimpedance between the transformer 607 and each meter, these are expectedto be negligible. (In this example, compare impedances 609+613 to meter627 with impedances 618+620 to meter 629.) If one meter, in this example627, sees a greater adjusted voltage drop than the other meters, withina tolerance representing normal differences in the line impedance, thenit is to be expected that an unmetered load exists between that meterand transformer 607.

Further, this method of comparing current and voltage from eachavailable “viewpoint” detects theft in the TAN even if there aremultiple theft points. Even if there were an unmetered load attachedbetween every meter and the transformer, unless the impedances 612, 623,etc. due to unauthorized loads were identical at all times, then thetheft points could still be inferred by a monitoring agent with accessto the current and voltage measurements of each measurement agent,because the voltage drops at some measurement points would not beproportional to the current at the same point.

When the monitoring agent residing at the Remote Hub of the TAN detectsa probable theft, then the Remote Hub may send an Edge-to-Substationmessage to alert the utility about the anomaly. Edge-to-Substationmessages, as described in U.S. patent application Ser. No. 13/871,944referenced above, travel from a Remote Hub to an electrical distributionsubstation supplying power to the substation transformer, here,transformer 607. From the substation, the message is transferred by aconventional network to a data center provided by the utility or anenergy management services provider. A theft alert may also bepropagated via another available network connected to the Remote Hub orother communicating meter, such as an AMI network. Such a message mayinclude at least a unique identifier of the service transformer or ameter at which the anomalous current-voltage relationship was detectedwhich may be used to match the origin of the message with the data in agrid map database.

The method described herein above with minor computational adjustmentscan be equally applied to a transformer area which has a bus topologysuch as is shown in FIG. 2 rather than a radial topology like FIGS. 1and 3. In a bus topology, the voltage drop from transformer to meter isadditive as each node is further from the transformer, as the meteredloads are connected in series rather than in parallel. Nevertheless,each metered load's contribution to the voltage drop ought to beproportional to the current being drawn at each meter. If the voltagedrop at a given meter is greater than proportional to the measuredcurrents between the transformer and that meter, based on the timestamped current and voltage measurements shared on the TAN by the othermeters—in this case, specifically the meters earlier in the series withrespect to the transformer than the given measurement point.

In order to apply this method in a TAN with a bus topology, it isnecessary for the order of the nodes in the TAN with respect to thetransformer to be known to the monitoring agent (at least). This can beinferred by the monitoring agent. The ordering of the series willcorrespond to the measured voltage at each metered point, with thelowest voltage being schematically furthest from the transformer.Referring again to FIG. 2, the schematically nearest meter totransformer 201 is 206, and the furthest in series is 208. This wouldremain true even if premise 205 were geospatiaily closer to transformer201 than premise 203, which is certainly possible. This condition isalso illustrated in FIG. 2. Additionally, this schematic inferenceremains correct even if power theft is occurring, because the resultingvoltage drops are still cumulative.

U.S. patent application Ser. Nos. 13/871,944, 13/888,102, and13/911,849, all referenced above, teach methods for recording anaccurate grid map of an electrical distribution network. The gridmapping method taught by these inventions includes the feeder and phaseof each substation operable to power each metered load supplied by thenetwork and a correct and current partitioning of the meters of thenetwork into Transformer Area Networks. In order to perform theftdetection, the grid map of a TAN with a bus topology may be augmentedwith the series order of the meters of the TAN, and this order can bekept up-to-date as meters and loads are added and removed from the TAN.For theft detection, this information may only need to be maintained bya monitoring agent in each TAN, and indeed it may be recomputedperiodically by each monitoring agent. However, it may be beneficial torecord this additional information in a centralized grid map database,said centralized grid map database being taught by Ser. No. 13/871,944.To do this, the Edge-to-Substation message sent when a new node isdiscovered in the TAN may include the schematic order of the meter onthe power line bus from the transformer. Similarly, if the order ofnodes were observed to change, for example after a power outage orextension of the TAN due to construction, then the new ordering might bereported in an Edge-to-Substation message to be recorded in a grid mapdatabase.

Another method of power theft is sometimes used that does not involvecreating an illegal tap. This method involves creating misdirection byswitching meters with a neighbor prior to making an increase inconsumption. A communicating meter of any kind can already be enabled toreport being disconnected from the meter socket if it is plugged into ameter socket again (whether the same socket or a different one) whilepower is available. However, an enterprising power thief can wait for anatural power outage in which to swap meters with another premise, orcan vandalize the network to create an outage in which to effect theswap. An intelligent meter, however, that participates in a TransformerArea Network with real-time grid mapping as is described herein and inthe referenced related inventions, can detect an illegal move in avariety of ways:

-   -   If two meters are swapped between two distinct TANs, then both        TANs may report discovering a new meter and losing        communications with a meter that was formerly part of the TAN.    -   If two meters are swapped in such a way that the phase of the        meters is reversed, then this change may be reported by the grid        mapping agents.    -   If two meters are switched within the same TAN and the same        phase, then it the TAN has a bus architecture, both meters will        be detected as having changed positions with respect to their        service transformer, and this may be reported by the monitoring        agent.    -   If a meter has access to a geospatial location signal, then a        grid mapping agent on the meter may report the change in        location.

This leaves only one case swapping two meters not enabled to receive ageospatial location signal, between two premises on the same phase ofthe same radial TAN—which is not easily detected. This case may beundesirable from the viewpoint of the thief because of the proximity ofthe premises better to tamper with a meter socket several blocks awaythan with that of the next-door neighbor.

Referring to FIG. 7, to manage the detection process, an agent such asthe monitoring agent on at least one communicating meter 700 (such as aRemote Hub) on each TAN 702 may report each of the detected anomalousconditions using an Edge-to-Substation message or another availablewide-area network 704 capable of forwarding the message to a softwareprogram 706 residing in a data center with access to the consolidatedgrid map. The software program 706 also receives reports of planned gridchanges from other applications used to manage the grid. An example ofsuch reports could be the work orders used to dispatch field engineersto make required changes and repairs to the distribution grid. Thesoftware program 706 avoids reporting false theft indications bymatching the anomaly reports from the communicating meters 700 againstthe work orders or similar reports. Anomalies which are explained by thework orders are not reported as potential indicators of theft. Theanomalies which cannot be matched with a work order create alerts that apotential theft may be occurring, regardless of whether the anomaly is achange in the grid map or a voltage anomaly reported by a monitoringagent. The theft alert may contain the account numbers and addresses ofthe affected premises, the identity and geospatial coordinates of theaffected transformers and meters, and any other relevant informationthat may be used to locate the theft, whether the theft is perpetratedby means of moving meters or by means of creating an unauthorized,unmetered tap.

The foregoing description of the invention has been presented forpurposes of illustration and description and is not intended to beexhaustive or to limit the invention to the precise forms disclosed.Many modifications and variations are possible in light of the aboveteaching. The embodiments were chosen and described in order to bestexplain the principles of the invention and its practical application tothereby enable others skilled in the art to best utilize the inventionin various embodiments and with various modifications as are suited tothe particular use contemplated. It is intended that the scope of theinvention be defined by the claims appended hereto.

The invention claimed is:
 1. A method comprising: receiving, by acomputing device, notifications from one or more utility applicationsregarding planned hardware changes in one of a plurality of TransformerArea Networks of an electrical distribution network associated with agrid mapping database, the one of a plurality of Transformer AreaNetworks comprising a first communicating meter and a secondcommunicating meter, the first communicating meter comprising aMeasurement Agent and a Monitoring Agent, the Measurement Agentconfigured to periodically measure and record a current, a voltage, anda time, the Monitoring Agent configured to receive and compare currentand voltage measurements taken at different meters at a same time;receiving, by the first communicating meter comprising a processordevice via the one of a plurality of Transformer Area Networks, ashort-range on-grid transmission from the second communicating meter,the first communicating meter and the second communicating meter coupledto the electrical distribution network on a low-voltage side of aservice transformer; detecting, by the first communicating meter of theone of a plurality of Transformer Area Networks, an anomalous conditionbased on the short-range on-grid transmission from the secondcommunicating meter; transmitting, by the first communicating meter, along-range on-grid message to the computing device, that identifies adetected hardware change based on the detected anomalous conditionwithin the one of a plurality of Transformer Area Networks of theelectrical distribution network; determining, by the computing device,that the detected hardware change is not identified in the notificationsregarding the one of a plurality of Transformer Area Networks; andinitiating, by the computing device, an alert that identifies thedetected hardware change.
 2. The method of claim 1, wherein thelong-range on-grid message identifying the detected hardware changeindicates an identity and a grid location of a new meter joining the oneof a plurality of Transformer Area Networks.
 3. The method of claim 1,wherein the long-range on-grid message identifying the detected hardwarechange indicates that a meter has stopped communicating with the one ofa plurality of Transformer Area Networks, the long-range on-grid messageidentifying the meter, and wherein the alert includes an identity and agrid location of the meter.
 4. The method of claim 1, wherein thelong-range on-grid message identifying the detected hardware changeindicates that a meter has changed location within the one of aplurality of Transformer Area Networks, the long-range on-grid messageidentifying the meter, and wherein the alert includes a messagereporting that a schematic location of the meter within a bus-structuredTransformer Area Network has changed.
 5. The method of claim 1, whereinthe long-range on-grid message identifying the detected hardware changeindicates that a geospatial location of a meter has changed.
 6. Themethod of claim 1, wherein the long-range on-grid message identifyingthe detected hardware change indicates that a power theft due to anunauthorized, unmetered tap may be occurring in the one of a pluralityof Transformer Area Networks.
 7. The method of claim 1, wherein theanomalous condition comprises an anomalous electrical condition.
 8. Themethod of claim 1, wherein the anomalous condition comprises ananomalous current-voltage relationship.
 9. The method of claim 1,wherein the anomalous condition comprises the one of a plurality ofTransformer Area Networks reporting losing communication with a formermeter and discovering a new meter.
 10. The method of claim 1, whereinthe anomalous condition comprises a phase change measured by the secondcommunicating meter.
 11. The method of claim 1, wherein the anomalouscondition comprises a change in position of the second communicatingmeter relative to the service transformer.
 12. The method of claim 1,wherein the anomalous condition comprises a change in location of thesecond communicating meter based on a geospatial location signal. 13.The method of claim 1, wherein the long-range on-grid message comprisesan Edge-to-Substation message.
 14. A system, comprising: a firstcommunicating meter on a low voltage side of a service transformer, thefirst communicating meter comprising a processor device configured to:receive, by the first communicating meter via a one of a plurality ofTransformer Area Networks of an electrical distribution network, ashort-range on-grid transmission from a second communicating meter, thefirst communicating meter and the second communicating meter coupled tothe electrical distribution network on a low-voltage side of the servicetransformer, the one of a plurality of Transformer Area Networkscomprising the first communicating meter and the second communicatingmeter, the first communicating meter comprising a Measurement Agent anda Monitoring Agent, the Measurement Agent configured to periodicallymeasure and record a current, a voltage, and a time, the MonitoringAgent configured to receive and compare current and voltage measurementstaken at different meters at a same time; detect, by the firstcommunicating meter of the one of a plurality of Transformer AreaNetworks, an anomalous condition based on the short-range on-gridtransmission from the second communicating meter; and transmit, by thefirst communicating meter, a long-range on-grid message that identifiesa detected hardware change based on the detected anomalous conditionwithin the one of a plurality of Transformer Area Networks of theelectrical distribution network; and a computing device comprising: acommunication interface configured to communicate with a network; and aprocessor coupled to the communication interface and configured to:receive notifications from one or more utility applications regardingplanned hardware changes in the one of a plurality of Transformer AreaNetworks of the electrical distribution network associated with a gridmapping database; receive the long-range on-grid message originated bythe first communicating meter; determine that the detected hardwarechange is not identified in the notifications regarding the one of aplurality of Transformer Area Networks; and initiate an alert thatidentifies the detected hardware change.
 15. The system of claim 14,wherein the long-range on-grid message identifying the detected hardwarechange indicates an identity and a grid location of a new meter joiningthe one of a plurality of Transformer Area Networks.
 16. The system ofclaim 14, wherein the long-range on-grid message identifying thedetected hardware change indicates that a meter has stoppedcommunicating with the one of a plurality of Transformer Area Networks,the long-range on-grid message identifying the meter, and wherein thealert includes an identity and a grid location of the meter.
 17. Thesystem of claim 14, wherein the long-range on-grid message identifyingthe detected hardware change indicates that a meter has changed locationwithin the one of a plurality of Transformer Area Networks, thelong-range on-grid message identifying the meter, and wherein the alertincludes a message reporting that a schematic location of the meterwithin a bus-structured Transformer Area Network has changed.
 18. Thesystem of claim 14, wherein the long-range on-grid message identifyingthe detected hardware change indicates that a geospatial location of ameter has changed.
 19. The system of claim 14, wherein the long-rangeon-grid message identifying the detected hardware change indicates thata power theft due to an unauthorized, unmetered tap may be occurring inthe one of a plurality of Transformer Area Networks.
 20. The system ofclaim 14, wherein the anomalous condition comprises an anomalouselectrical condition.
 21. The system of claim 14, wherein the anomalouscondition comprises an anomalous current-voltage relationship.
 22. Thesystem of claim 14, wherein the anomalous condition comprises the one ofa plurality of Transformer Area Networks reporting losing communicationwith a former meter and discovering a new meter.
 23. The system of claim14, wherein the anomalous condition comprises a phase change measured bythe second communicating meter.
 24. The system of claim 14, wherein theanomalous condition comprises a change in position of the secondcommunicating meter relative to the service transformer.
 25. The systemof claim 14, wherein the anomalous condition comprises a change inlocation of the second communicating meter based on a geospatiallocation signal.
 26. The system of claim 14, wherein the long-rangeon-grid message comprises an Edge-to-Substation message.